کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
411371 679549 2016 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Prediction of protein-RNA interactions using sequence and structure descriptors
ترجمه فارسی عنوان
پیش بینی فعل و انفعالات پروتئین RNA با استفاده از توالی و توصیف گرهای ساختار
کلمات کلیدی
تعامل پروتئین، RNA؛ توالی و ساختار توصیف؛ گرایش تعامل؛ پیش بینی جنگل های تصادفی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• A novel computational method is proposed for predicting protein-RNA interactions.
• The efficiency and advantage are shown in multiple benchmarks and comparison studies.
• Case studies in protein-miRNA/lncRNA interactions demonstrate its powerful prediction ability.

Protein-RNA interactions play critical roles in numerous biological processes such as posttranscriptional regulation and protein synthesis. However, experimental screening of protein-RNA interactions is usually laborious and time-consuming. It is therefore desirable to develop efficient bioinformatics methods to predict protein-RNA interactions, which can provide valuable hints for future experimental design and advance our understanding of the interaction mechanisms. In this study, we propose a novel method for predicting protein-RNA interactions based on both sequence and structure descriptors of protein and RNA (e.g., the sequence-based physicochemical features, the secondary and three-dimensional structure-based features). We train and compare several classifiers using these descriptors on several benchmark datasets, and the random forest method is selected to build an efficient predictor of protein-RNA interactions. We conduct further cross-validation and case studies, and the results clearly suggest the efficacy of the proposed method.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 206, 19 September 2016, Pages 28–34
نویسندگان
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